Floods are major natural disasters that have considerable consequences worldwide. As the frequency and magnitude of flooding are expected to be affected by ongoing climate change, understanding their past changes is important for developing adequate adaptation measures. However,
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Floods are major natural disasters that have considerable consequences worldwide. As the frequency and magnitude of flooding are expected to be affected by ongoing climate change, understanding their past changes is important for developing adequate adaptation measures. However, the limited spatiotemporal coverage of flood gauges hinders detection of changes in flooding, particularly in poorly gauged regions. Here, we propose a method using surface water data of river floodplain inundation as a proxy of the magnitude and frequency of flooding. Surface water data − Aqua Monitor which represented the probability linear trend changes in land and water surface area based on 30-m Landsat images between 1984–2000 and 2000–2013 was used in this study. The changes in water surface area over the floodplain obtained from Aqua Monitor showed high correspondence with historical trends observed or simulated annual maximum daily discharge, indicating the potential to detect changes in frequency and magnitude of flood from satellite data. In regions where changes could be measured with sufficient satellite images, 29% showed an increase in water surface area in the flood plain, 41% showed a decrease, and 30% showed small or no changes.
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